Coastal upwelling and downwelling forcing of circulation in a semi-enclosed bay: Ria de Vigo

Semi-enclosed bays in upwelling regions are exposed to forcing related to winds, currents and buoyancy over the shelf. The influence of this external forcing is moderated by factors such as connectivity to the open ocean, shelter by surrounding topography, dimensions of the bay, and freshwater outflows. Such bays, preferred locations for ports, mariculture, marine industry, recreational activities and coastal settlement, present a range of characteristics, understanding of which is necessary to their rational management. Observations in such a semi-enclosed bay, the Ria de Vigo in Spain, are used to characterize the influence of upwelling and downwelling pulses on its circulation. In this location, near the northern limit of the Iberian upwelling system, upwelling events dominate during a short summer season and downwelling events the rest of the year. The ria response to the external forcing is central to nutrient supply and resultant plankton productivity that supports its high level of cultured mussel production. Intensive field studies in September 2006 and June 2007 captured a downwelling event and an upwelling event, respectively. Data from eight current profiler moorings and boat-based MiniBat/ADCP surveys provided an unprecedented quasi-synoptic view of the distribution of water masses and circulation patterns in any ria. In the outer ria, circulation was dominated by the introduction of wind-driven alongshore flow from the external continental shelf through the ria entrances and its interaction with the topography. In the middle ria, circulation was primarily related to the upwelling/downwelling cycle, with a cool, salty and dense lower layer penetrating to the inner ria during upwelling over the shelf. A warmer, lower salinity and less dense surface layer of coastal waters flowed inward during downwelling. Without external forcing, the inner ria responded primarily to tides and buoyancy changes related to land runoff. Under both upwelling and downwelling conditions, the flushing of the ria involved shelf responses to wind pulses. Their persistence for a few days was sufficient to allow waters from the continental shelf to penetrate the innermost ria. Longer term observations supported by numerical modeling are required to confirm the generality of such flushing events in the ria and determine their typical frequency, while comparative studies should explore how these scenarios fit into the range of conditions experienced in other semi-enclosed bays

Efficient singlet exciton fission in pentacene prepared from a soluble precursor

Carrier multiplication using singlet exciton fission (SF) to generate a pair of spin-triplet excitons from a single optical excitation has been highlighted as a promising approach to boost the photocurrent in photovoltaics (PVs) thereby allowing PV operation beyond the Shockley-Queisser limit. The applicability of many efficient fission materials, however, is limited due to their poor solubility. For instance, while acene-based organics such as pentacene (Pc) show high SF yields (up to 200%), the plain acene backbone renders the organic molecule insoluble in common organic solvents. Previous approaches adding solubilizing side groups such as bis(tri-$\textit{iso}$-propylsilylethynyl) to the Pc core resulted in low vertical carrier mobilities due to reduction of the transfer integrals via steric hindrance, which prevented high efficiencies in PVs. Here we show how to achieve good solubility while retaining the advantages of molecular Pc by using a soluble precursor route. The precursor fully converts into molecular Pc through thermal removal of the solubilizing side groups upon annealing above 150 °C in the solid state. The annealed precursor shows small differences in the crystallinity compared to evaporated thin films of Pc, indicating that the Pc adopts the bulk rather than surface polytype. Furthermore, we identify identical SF properties such as sub-100 fs fission time and equally long triplet lifetimes in both samples.M.T. thanks the Gates Cambridge Trust and the Winton Programme for the Physics of Sustainability for funding. A.H.K. acknowledges the Cambridge Nehru Bursary, the Cambridge Bombay Society, a Trinity-Henry Barlow- and Haidar Scholarship as well as Rana Denim Pvt. Ltd. for financial support. K.B. and J.N. would like to thank Dr. Tom Arnold and Jakub Rozboril for assistance during the beam time at Diamond Light Source. Financial support for K.B. from Diamond Light Source, Swiss Light Source, and the German Research Foundation (Grant No. BR 4869/1-1) is gratefully acknowledged. M.L.B. is a research fellow of Christ’s College, Cambridge. This work was supported by the Engineering and Physical Sciences Research Council (Grant Nos. EP/M005143/1, EP/G060738/1 and Cambridge NanoDTC EP/G037221/1, EP/L015978/1)

Phylogenetic tree information aids supervised learning for predicting protein-protein interaction based on distance matrices

BACKGROUND: Protein-protein interactions are critical for cellular functions. Recently developed computational approaches for predicting protein-protein interactions utilize co-evolutionary information of the interacting partners, e.g., correlations between distance matrices, where each matrix stores the pairwise distances between a protein and its orthologs from a group of reference genomes. RESULTS: We proposed a novel, simple method to account for some of the intra-matrix correlations in improving the prediction accuracy. Specifically, the phylogenetic species tree of the reference genomes is used as a guide tree for hierarchical clustering of the orthologous proteins. The distances between these clusters, derived from the original pairwise distance matrix using the Neighbor Joining algorithm, form intermediate distance matrices, which are then transformed and concatenated into a super phylogenetic vector. A support vector machine is trained and tested on pairs of proteins, represented as super phylogenetic vectors, whose interactions are known. The performance, measured as ROC score in cross validation experiments, shows significant improvement of our method (ROC score 0.8446) over that of using Pearson correlations (0.6587). CONCLUSION: We have shown that the phylogenetic tree can be used as a guide to extract intra-matrix correlations in the distance matrices of orthologous proteins, where these correlations are represented as intermediate distance matrices of the ancestral orthologous proteins. Both the unsupervised and supervised learning paradigms benefit from the explicit inclusion of these intermediate distance matrices, and particularly so in the latter case, which offers a better balance between sensitivity and specificity in the prediction of protein-protein interactions

ERP evidence suggests executive dysfunction in ecstasy polydrug users

Background: Deficits in executive functions such as access to semantic/long-term memory have been shown in ecstasy users in previous research. Equally, there have been many reports of equivocal findings in this area. The current study sought to further investigate behavioural and electro-physiological measures of this executive function in ecstasy users. Method: Twenty ecstasy–polydrug users, 20 non-ecstasy–polydrug users and 20 drug-naïve controls were recruited. Participants completed background questionnaires about their drug use, sleep quality, fluid intelligence and mood state. Each individual also completed a semantic retrieval task whilst 64 channel Electroencephalography (EEG) measures were recorded. Results: Analysis of Variance (ANOVA) revealed no between-group differences in behavioural performance on the task. Mixed ANOVA on event-related potential (ERP) components P2, N2 and P3 revealed significant between-group differences in the N2 component. Subsequent exploratory univariate ANOVAs on the N2 component revealed marginally significant between-group differences, generally showing greater negativity at occipito-parietal electrodes in ecstasy users compared to drug-naïve controls. Despite absence of behavioural differences, differences in N2 magnitude are evidence of abnormal executive functioning in ecstasy–polydrug users

Multiple Local and Recent Founder Effects of TGM1 in Spanish Families

<div><h3>Background</h3><p>Mutations in the <em>TGM1</em> gene encoding transglutaminase 1 are a major cause of autosomal recessive congenital ichthyosis. In the Galician (NW Spain) population, three mutations, c.2278C>T, c.1223_1227delACAC and c.984+1G>A, were observed at high frequency, representing ∼46%, ∼21% and ∼13% of all <em>TGM1</em> gene mutations, respectively. Moreover, these mutations were reported only once outside of Galicia, pointing to the existence of historical episodes of local severe genetic drift in this region.</p> <h3>Methodology/Principal Findings</h3><p>In order to determine whether these mutations were inherited from a common ancestor in the Galician population, and to estimate the number of generations since their initial appearance, we carried out a haplotype-based analysis by way of genotyping 21 SNPs within and flanking the <em>TGM1</em> gene and 10 flanking polymorphic microsatellite markers spanning a region of 12 Mb. Two linkage disequilibrium based methods were used to estimate the time to the most recent common ancestor (TMRCA), while a Bayesian-based procedure was used to estimate the age of the two mutations. Haplotype reconstruction from unphased genotypes of all members of the affected pedigrees indicated that all carriers for each of the two mutations harbored the same haplotypes, indicating common ancestry.</p> <h3>Conclusions/Significance</h3><p>In good agreement with the documentation record and the census, both mutations arose between 2,800–2,900 years ago (y.a.), but their TMRCA was in the range 600–1,290 y.a., pointing to the existence of historical bottlenecks in the region followed by population growth. This demographic scenario finds further support on a Bayesian Coalescent Analysis based on <em>TGM1</em> haplotypes that allowed estimating the occurrence of a dramatic reduction of effective population size around 900–4,500 y.a. (95% highest posterior density) followed by exponential growth.</p> </div

Cognitive impairment induced by delta9-tetrahydrocannabinol occurs through heteromers between cannabinoid CB1 and serotonin 5-HT2A receptors

Delta-9-tetrahydrocannabinol (THC), the main psychoactive compound of marijuana, induces numerous undesirable effects, including memory impairments, anxiety, and dependence. Conversely, THC also has potentially therapeutic effects, including analgesia, muscle relaxation, and neuroprotection. However, the mechanisms that dissociate these responses are still not known. Using mice lacking the serotonin receptor 5-HT2A, we revealed that the analgesic and amnesic effects of THC are independent of each other: while amnesia induced by THC disappears in the mutant mice, THC can still promote analgesia in these animals. In subsequent molecular studies, we showed that in specific brain regions involved in memory formation, the receptors for THC and the 5-HT2A receptors work together by physically interacting with each other. Experimentally interfering with this interaction prevented the memory deficits induced by THC, but not its analgesic properties. Our results highlight a novel mechanism by which the beneficial analgesic properties of THC can be dissociated from its cognitive side effects

The ADAMTS (A Disintegrin and Metalloproteinase with Thrombospondin motifs) family

The ADAMTS (A Disintegrin and Metalloproteinase with Thrombospondin motifs) enzymes are secreted, multi-domain matrix-associated zinc metalloendopeptidases that have diverse roles in tissue morphogenesis and patho-physiological remodeling, in inflammation and in vascular biology. The human family includes 19 members that can be sub-grouped on the basis of their known substrates, namely the aggrecanases or proteoglycanases (ADAMTS1, 4, 5, 8, 9, 15 and 20), the procollagen N-propeptidases (ADAMTS2, 3 and 14), the cartilage oligomeric matrix protein-cleaving enzymes (ADAMTS7 and 12), the von-Willebrand Factor proteinase (ADAMTS13) and a group of orphan enzymes (ADAMTS6, 10, 16, 17, 18 and 19). Control of the structure and function of the extracellular matrix (ECM) is a central theme of the biology of the ADAMTS, as exemplified by the actions of the procollagen-N-propeptidases in collagen fibril assembly and of the aggrecanases in the cleavage or modification of ECM proteoglycans. Defects in certain family members give rise to inherited genetic disorders, while the aberrant expression or function of others is associated with arthritis, cancer and cardiovascular disease. In particular, ADAMTS4 and 5 have emerged as therapeutic targets in arthritis. Multiple ADAMTSs from different sub-groupings exert either positive or negative effects on tumorigenesis and metastasis, with both metalloproteinase-dependent and -independent actions known to occur. The basic ADAMTS structure comprises a metalloproteinase catalytic domain and a carboxy-terminal ancillary domain, the latter determining substrate specificity and the localization of the protease and its interaction partners; ancillary domains probably also have independent biological functions. Focusing primarily on the aggrecanases and proteoglycanases, this review provides a perspective on the evolution of the ADAMTS family, their links with developmental and disease mechanisms, and key questions for the future

Standards for the Characterization of Endurance in Resistive Switching Devices

Resistive switching (RS) devices are emerging electronic components that could have applications in multiple types of integrated circuits, including electronic memories, true random number generators, radiofrequency switches, neuromorphic vision sensors, and artificial neural networks. The main factor hindering the massive employment of RS devices in commercial circuits is related to variability and reliability issues, which are usually evaluated through switching endurance tests. However, we note that most studies that claimed high endurances >106 cycles were based on resistance versus cycle plots that contain very few data points (in many cases even <20), and which are collected in only one device. We recommend not to use such a characterization method because it is highly inaccurate and unreliable (i.e., it cannot reliably demonstrate that the device effectively switches in every cycle and it ignores cycle-to-cycle and device-to-device variability). This has created a blurry vision of the real performance of RS devices and in many cases has exaggerated their potential. This article proposes and describes a method for the correct characterization of switching endurance in RS devices; this method aims to construct endurance plots showing one data point per cycle and resistive state and combine data from multiple devices. Adopting this recommended method should result in more reliable literature in the field of RS technologies, which should accelerate their integration in commercial products

SPPS: A Sequence-Based Method for Predicting Probability of Protein-Protein Interaction Partners

Background: The molecular network sustained by different types of interactions among proteins is widely manifested as the fundamental driving force of cellular operations. Many biological functions are determined by the crosstalk between proteins rather than by the characteristics of their individual components. Thus, the searches for protein partners in global networks are imperative when attempting to address the principles of biology. Results: We have developed a web-based tool ‘‘Sequence-based Protein Partners Search’ ’ (SPPS) to explore interacting partners of proteins, by searching over a large repertoire of proteins across many species. SPPS provides a database containing more than 60,000 protein sequences with annotations and a protein-partner search engine in two modes (Single Query and Multiple Query). Two interacting proteins of human FBXO6 protein have been found using the service in the study. In addition, users can refine potential protein partner hits by using annotations and possible interactive network in the SPPS web server. Conclusions: SPPS provides a new type of tool to facilitate the identification of direct or indirect protein partners which may guide scientists on the investigation of new signaling pathways. The SPPS server is available to the public a

Critical assessment of sequence-based protein-protein interaction prediction methods that do not require homologous protein sequences

<p>Abstract</p> <p>Background</p> <p>Protein-protein interactions underlie many important biological processes. Computational prediction methods can nicely complement experimental approaches for identifying protein-protein interactions. Recently, a unique category of sequence-based prediction methods has been put forward - unique in the sense that it does not require homologous protein sequences. This enables it to be universally applicable to all protein sequences unlike many of previous sequence-based prediction methods. If effective as claimed, these new sequence-based, universally applicable prediction methods would have far-reaching utilities in many areas of biology research.</p> <p>Results</p> <p>Upon close survey, I realized that many of these new methods were ill-tested. In addition, newer methods were often published without performance comparison with previous ones. Thus, it is not clear how good they are and whether there are significant performance differences among them. In this study, I have implemented and thoroughly tested 4 different methods on large-scale, non-redundant data sets. It reveals several important points. First, significant performance differences are noted among different methods. Second, data sets typically used for training prediction methods appear significantly biased, limiting the general applicability of prediction methods trained with them. Third, there is still ample room for further developments. In addition, my analysis illustrates the importance of complementary performance measures coupled with right-sized data sets for meaningful benchmark tests.</p> <p>Conclusions</p> <p>The current study reveals the potentials and limits of the new category of sequence-based protein-protein interaction prediction methods, which in turn provides a firm ground for future endeavours in this important area of contemporary bioinformatics.</p